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原文連結
論文資訊
- 類型：已發表論文
- 日期：2022
摘要
Systems neuroscience is facing an ever-growing mountain of data. Recent advances in 蛋白質 engineering and microscopy have together led to a paradigm shift in neuroscience; using fluorescence, we can now image the activity of every neuron through the whole 大腦 of behaving animals. Even in larger organisms, the number of neurons that we can record simultaneously is increasing exponentially with time. This increase in the dimensionality of the data is being met with an explosion of 計算 and 數學 methods, each using disparate terminology, distinct approaches, and diverse 數學 concepts. Here we collect, organize, and explain multiple data analysis techniques that have been, or could be, applied to whole-大腦 imaging, using larval zebrafish as an example model. We begin with methods such as linear regressi
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